Future framing in advertising : the effects of future framing in ads on both explicit and implicit attitudes and intention, strengthened by the amount of elaboration on the ad

“

Future Framing in Advertising”

The effects of future framing in ads on both explicit and implicit attitudes and intention, strengthened by the amount of elaboration on the ad

MSc Thesis, Graduate School of Communication Science University of Amsterdam

By MSc student in Persuasive Communication

Huub Schuijn

10494510

Supervisors:

A.M. Wennekers – Assistant professor Persuasive Communication S.C.M Welten – Assistant professor Persuasive Communication

ABSTRACT

Future framing is a persuasive communication strategy whereby the future release date of a product is emphasized in advertising. According to Construal Level Theory (CLT), it is expected that display of ‘future framed’ ads induces more positive thoughts and feelings about the ad and product, compared to ‘current framed’ ads. However, it remains unclear how future framed ads exactly are affecting consumer behavior. Studies have measured positive effects of future framed ads on consumer attitudes and intentions, by explicitly instructing people to list thoughts and feelings they have watching future framed ads. However, in real life situations, consumers cannot elaborate on all persuasive messages they encounter, due to advertising clutter. This study measured the effects of future framed ads on both explicit and implicit consumer attitudes and intention and measured the possible effects of elaboration instructions using a systematic approach. In an online experiment, participants were randomly assigned to a condition where they either viewed a future framed or a current framed ad, and either were instructed to list thoughts and indicate feelings, or were not instructed at all. After a self-report on explicit attitudes and intention, participants performed an Affect Misattribution Procedure (AMP) to measure implicit attitudes. The experiment concluded with an implicit choice test. Results indicate no differences in effects of future framed ads on both explicit and implicit attitudes and intention, compared to current framed ads. Elaboration did not influence the strength of the future framing effects. However, the absence of elaboration instructions had a significant positive effect on implicit attitudes towards the product. Concluding, the results of the effects of future framing in this study were opposing to the outcomes of previous studies. Further research is needed to get better understanding of future framing effects in advertising, on both explicit as implicit consumer attitudes and intention.

INTRODUCTION

During the 79th Academy Awards, that took place on February 25, 2007, the first iPhone ad was aired on television. The ad featured clips from dozens of notable films and television shows over the last 70 years, showing iconic characters answering phones. The iPhone is shown at the end with the caption: "Hello. Coming in June" (Sharma, Wingfield, & Yuan, 2007; Burrows, 2008). The interesting fact is that the iPhone was not launched by the time the commercial aired and this was emphasized in the ad. Apple’s strategy, to communicate intensively about their new product before its launch, received much attention during and after the campaign (Dahlén, 2008; Sharma et al., 2008). It was seen as a game changer in advertising, since it was not very common in the field of marketing to advertise products that still have to be launched in the future (Sharma et al., 2008). Most communication research by that time focused on how and when to communicate about a product after its release (Cannon, Leckenby, & Abernethy, 2002; Franses & Vroomen, 2006). Besides, it was believed that advertising of pre-launched products brings unfortunate effects, particularly in high-tech industries, as they cue competitors on what is waiting down the line and give them time to react (Sorescu, Shankar, & Kushwaha, 2007; Mohr, Sengupta, & Slater, 2010; Gerhard, Brem, & Baccarella, 2011). Nonetheless, Apple’s communication strategy proved otherwise. Over 70 million Google search hits for the product prior to its launch testified the great consumer interest for the iPhone as result of the communication by Apple (Dahlén, Thorbjønsen, & Sjödin, 2011).

The effects of communicating about to-be-released or future products became an instant relevant topic in persuasive communication science. The book “Nextopia” (Dahlén, 2008) could be described as the peak of the hype around ‘future framing’ in advertising. ‘Nextopia’ proposes that consumers will perceive the next product, event or experience as more pleasant or desirable when it is positioned as a future, to-be-released product in the advertising strategy (Dahlén, 2008). It was theorized that consumers have a ‘future’ bias and they predominantly prefer products that are advertised before they are launched (‘available

from…’) to identical products that are ‘in stores now’; even if the product is a simple bottle of

water (Dahlén et al., 2011). Subsequently, it was suggested that the use of such ‘future framing’, e.g. emphasizing a future release date, in advertising would be a powerful communication tool to persuade consumers to boost sales of products and services.

However, it is difficult to conceive how future framing in advertising exactly is affecting consumer behavior. Studies to date have tried to measure the effects of future framing in advertising on consumer attitudes and purchase intentions, by explicitly instructing people to list the thoughts they have watching future framed ads, or to forecast how happy they would feel if they were to use the advertised product in the future (Dahlén et al., 2011).

However, in real life situations, people have to process over 600 ads on a daily basis (Anderson & De Palma, 2013). It is therefore very unlikely that consumers form conscious thoughts or forecasted feelings about all these ads. And most likely, there will not be someone to stand next to each ad to instruct the consumer to elaborate on it by listing thoughts or feelings. What would the effects of future framing on consumer behavior be, when a consumer is in a situation without instructions that might induce elaboration on the ad’s message? In other words, could the found effects of future framing be (partly) described to the fact that participants in previous experiments were instructed to elaborate more on the persuasive message of the ad?

This study will measure the effects of future framing in advertisements on consumer attitudes and intention, and more importantly, will measure the possible effects of elaboration inducing instructions (e.g. thought-listing and forecasting) using a systematic approach. Besides, an exploratory study on implicit and more associative effects of future framing on consumer behavior will follow. Moreover, this study will be the first attempt to measure the effects of future framing on implicit attitudes and intention.

THEORETICAL BACKGROUND

Because this study will measure the effects of future framing in advertisements on consumer attitudes and intention in a way similar to the research of Dahlén et al. (2011), I focus on how they hypothesized their expectations based on existing theory. The studies of Dahlén et al. (2011) focused on consumer psychology research on the optimism bias, positive uncertainty, and affective (mis-) forecasting. To get a thorough understanding of these theories, they will be held against the light of the Construal Level Theory (CLT), the social psychological theory on which the optimism bias, positive uncertainty and forecasting theories are based. I will explain CLT below, guided by the assumptions Dahlén and colleagues made in their studies as subheadings of each paragraph.

Construal Level Theory (CLT)

The mental representation of things, events and persons depends on perceived psychological distance to these objects (Lewin, 1951). Distance could be perceived in terms of both space and time. Perceived distance, temporal distance in particular, between individuals and all other things in their surroundings, affects predictions, evaluations and behavior (Fujita, Henderson, Trope, & Liberman, 2006; Trope & Liberman, 2003; Kim, Zhang, & Li, 2008; Bar-Anan, Liberman, & Trope, 2006; Henderson, Trope, & Carnevale, 2006).

The way we experience temporal distance determines the abstraction of our thoughts (Trope & Liberman, 1998). Thoughts about things, events and people that are perceived as

distant from our selves (in time) are construed in a more abstract, ‘high-level’ fashion (the

forest); when the distance is perceived as proximate, thoughts are construed more concrete, ‘low-level’ and detailed (the trees) (Trope & Liberman, 2003). This is the basis of the

Construal Level Theory (CLT).

The optimism bias: “Things in the future are more abstract, thus more positive”

Every product is defined by a set of attributes or features. People categorize and prioritize attributes and base their choices on this attribute weighing (Tyebjee, 1987; Martin, Gnoth, & Strong, 2009). Primary product attributes (e.g. ‘why do I want to use this?’) are associated with high-level thoughts and secondary product attributes (e.g. ‘how much does it cost me to

use this?’) are associated with low-level thoughts (Stephan, Liberman, & Trope, 2011;

Liberman, Sagristano, & Trope, 2002). Subsequently, when objects are situated further in time, the primary object attributes (why) are given more weight than the secondary attributes (how). When an object is situated closer in time, the secondary attributes will become more salient.

Accordingly, events distant in time seem to be evaluated based on positive attributes and near events are evaluated more on the basis of negative attributes. As benefits are likely to be construed as high-level thoughts and costs as low-level thoughts, it is feasible to state that products or events will always be evaluated more favorably in the distant future than in the near future, if they have both positive and negative attributes (Eyal, Liberman, Trope & Walter, 2004; Herzog, Hansen, & Wänke, 2007).

The tendency for people to be overly optimistic about the outcomes of their future behaviors is called the optimism bias, and is dependent on temporal distance, since people report greater optimism in forecasting the distant future than in forecasting the near future (Peterson, 2000; Gilovich, Kerr, & Medvec, 1993). It is the overestimation to have more positive outcomes than significant others and the lack of perception of vulnerability for possible negative outcomes (Ariely, 2009). In both retrospect and prospect, people overestimate the value of events compared to what they feel in the present (Mitchell, Thompson, Peterson, & Cronk, 1997; Dahlén, 2008). This future optimism is also seen in consumer related situations, where the promotion of temporally distant products induces higher product evaluations than the promotion of immediately available products (Dahlén et al., 2011). As stated earlier, people have the tendency to weigh benefits more heavily than costs when an event is in the far future (Eyal et al., 2004). So according to the CLT, people probably will have more positive expectations of objects in the distant future than in the near future.

Positive uncertainty: “More thoughts generated to reduce uncertainty of the future”

For consumers, the future is more uncertain than the present (Kahneman, Knetsch, & Thaler, 1991; Samuelson & Zeckhauser, 1988). Consumers prefer certainty to uncertainty (Wilson, Centerbar, Kermer, & Gilbert, 2005), and when encountering uncertainty the goal is to reduce it. A study following this logic found that greater uncertainty led to the use of more comprehensive information in product evaluations (Grant & Tybout, 2008). Applying these findings to advertising, future framed ads were processed more extensively than current framed ads because the future framed had more uncertainty and therefore the ad evoked a greater number of thoughts than the current ad (Dahlén et al., 2011).

Affective forecasting: “People believe to be happier in the future”

Most of people’s decisions, predictions and evaluations are based on the possible consequences of future outcomes. The predictions ought to be as accurate as possible to make the most efficient decisions. This strictly rational assumption was counter argued by Kahneman and Snell (1992). They argued that individuals are unable to predict the utility they will experience as result of a decision. They differentiated between a predicted and an

experienced utility, also measured in forecasted emotions. In forecasting the predicted utility,

people systematically overestimate the happiness they will feel in case of success, both in terms of intensity and duration (Kahneman & Snell, 1990; 1992; Wilson et al., 2000a; Gilbert et al., 1998; Ayton, Pott, Elwakili, 2007). Similarly, people find it hard to predict how their feelings will change over time and in which fashion their emotions will adapt to new situations (Kahneman & Snell, 1992; Weinstein, 1982). Dahlén and colleagues (2011) argue that this forecasting error proves that individuals are unable to learn from experience when it comes to predicting their feelings for similar experiences in the future.

From a consumer perspective, this forecasting bias implies that individuals tend to overrate joy each time they forecast feelings about future purchase experiences. It is therefore expected that consumers will overrate their forecasted feelings for future products compared to their actual emotions on the moment they actually purchase the product. Accordingly, Dahlén and colleagues (2011) showed that subjects to future framed ad stimuli reported stronger forecasted post-purchase feelings than subjects of current time framed ad stimuli. Based on these three assumptions, this hypothesis is formulated:

H1: Consumers confronted with a future framed ad have more positive ad and brand evaluations and a stronger intention to purchase the product, compared to consumers confronted with a current framed ad.

Inducing elaboration as result of thought-listing and affective forecasting

Considering the past studies about future framing by Dahlén and colleagues (2011), could the instructions of thought-listing and forecasting used as a means to measure the effects of future framing possibly have led to more elaboration on the ads? In other words, would the extensive thinking and imagining about the advertised product also have started when participants were not explicitly asked to think or imagine? And would a difference be found in the amount of thoughts and happy feelings between the participants exposed to a future framed ad and participants exposed to a current framed ad when they do not receive explicit instructions? Because of thought-listing and forecasting instructions during experiments and surveys, participants are induced to generate more thoughts about a product or event. These cognitive assignments force the participant to elaborate more about the subject (Banas, Turner, & Shulman, 2012; Baek, Cappella, & Bindman, 2011; Hoerger, Quirk, Lucas, & Carr, 2010; Cacioppo, Von Hippel, & Ernst, 1997).

According to the Elaboration Likelihood Model (ELM), consumers that elaborate more on a subject form stronger, longer lasting attitudes about this subject (Petty & Cacioppo, 1981; 1983; 1986a; 1984). As pointed earlier, the CLT states that thoughts about the future are more abstract and consumers tend to overestimate how positive these thoughts are. Moreover, their judgments about how positive or happy their future will be is influenced by these thoughts. An instruction to actively elaborate more on these ‘biased’ thoughts then could arguably lead to confounding results of the future frame effect on consumer attitudes. Thus, the thought-listing and forecasting instruction during experiments and surveys about future framing may influence the way the participants report their attitude, which consequently affects the reports on intention as well.

In real life, consumers have little time to process ad information. Most of the time, they will process ads based on heuristics and emotions. According to the ELM, emotions that influence behavior in the peripheral processing route are mostly unconscious (Petty & Cacioppo, 1983; Petty & Briñol, 2006). Therefore, consumers are not even aware they act upon their emotions. Regarding the ad clutter example of the 600 ads consumers have to process each day (Anderson & De Palma, 2013), it is reasonable that most of the ads have to be processed superficially, even when the ad concerns high involvement products (Berger & Mitchell, 1989). When there is no or less elaboration, it is expected that consumers will process ads in a superficial and heuristic way. It is expected that the absence of instructions lead to diminished effects of future framing on consumer attitudes, because consumers will elaborate less on the advertised messages. From the previous statements, the following hypothesis can be derived:

H2: Consumers explicitly instructed to list thoughts about advertisements and to forecast feelings about a product will have more positive ad and brand evaluations and a stronger purchase intention, compared to consumers who are not instructed H3: The hypothesized effects of future framing (see H1) on ad and brand evaluations and purchase intention will be stronger under the conditions with thought listing and forecasting instructions, compared to the conditions without instructions.

The conceptual research model of this study on evaluations and intention is presented in Figure 1 below. It is important to note that all the stated hypotheses concern the effects of future framing and instructions on explicit evaluations and intention. Consequently, this means that the hypotheses will be tested with explicit measures, meaning that consumers will be explicitly asked to indicate their evaluations and intention. However, studies on dual processing routes show that consumers are mostly not aware of their behavior with a more heuristic and associative nature (Kahneman & Snell, 1992; Petty & Cacioppo, 1984; Gawronksi & Bodenhausen, 2006). Therefore, consumers cannot indicate their implicit behavior. Furthermore, studies have found that stimuli can have different effects on explicit and implicit attitudes and intention (Bohner & Dickel, 2011). What effects do future framing and instructions have on implicit evaluations and intention and how might they differ from the effects on explicit evaluations and intention? In order to assess these effects on an implicit level, a more exploratory investigation will follow in this study.

Figure 1. Conceptual research model

Temporal Framing (Future vs Current) Ad evaluations Brand evaluations Purchase intention

Elaboration instructions: Thought listing and Forecasting

(YES vs NO) +   H1   H2   H3   +  

Exploratory idea of implicit attitude change

Research on dual-processing routes in coping with persuasive messages such as the ELM has further developed over the years, and new ways of thinking about dual processing have emerged. One of the renewed perspectives on dual processing is the associative-propositional

evaluative model (APE) (Gawronski & Bodenhausen, 2006; Bohner & Dickel, 2011). The

model suggests that attitudes can be changed or formed through either the mere association of a valenced stimulus with an attitude object or through more extensive propositional reasoning. The APE model gives insight into how two different coping processes lead to different kinds of attitude formation. The two types of coping processes are described below. Furthermore, the APE model states that in order to measure the attitudes formed as result of the process of propositional reasoning, explicit measures are required (e.g. self-report, questionnaires). For measuring attitudes formed by the process of associative evaluation, implicit measures (e.g. AMP, IAT) are required.

The process of propositional reasoning

As explained above, the APE model proposes two possible routes. The first route is the main processing route that results in explicit attitudes: attitudes that can be reported by participants in surveys. The underlying propositional reasoning of these attitudes is a mere cognitive process comparable with the central processing route of the ELM model (Gawronski & Bodenhausen, 2006; Petty & Briñol, 2006). Most of our explicit attitudes are based on propositional reasoning; if we are able to self-report attitudes, then we can think about them consciously, we can reason about them.

It could be expected that when participants are instructed to list their thoughts or to imagine a future product or event, they propositionally reason in favor of their consisting attitudes. According to the APE model, this propositional reasoning will strengthen the explicit attitudes. So, giving instructions leads to more propositional reasoning, which could lead to the formation of explicit attitudes.

The process of associative evaluation

The second route in the APE model presumes that when a consumer does not elaborate on the informational input, he or she implicitly associates the informational input with existing knowledge and memories. This route is comparable with the peripheral route of the ELM model (Petty & Briñol, 2006). However, an important difference between the ELM model and the APE model is the assumption that propositional reasoning could be affected by associative evaluation and vice versa in the APE model, and not in the ELM model. The associative evaluation route implicitly links the informational input to all existing associations the individual holds. It is likely that when participants in an experiment are not instructed to elaborate on their thoughts, they will still associatively evaluate information. However, it is

conceivable that a person has few to no associations with new products that are not even launched yet. Thoughts about the future may therefore be too abstract and do not rely on context enough. They might therefore be harder to associate with existing knowledge. Therefore, without elaboration and propositional reasoning a future frame might not be effective. Concluding, it is expected that future framing in the associative evaluation condition has no effect on implicit attitude formation. Therefore, in the exploratory study there will only be focus on testing the effects of instructions on both propositional reasoning and associative evaluation, followed by explicit and implicit attitude formation, respectively.

Without the instructions of thought listing and forecasting, there probably will be less propositional reasoning and more associative evaluation. Leaving instructions out would possibly lead to more positive implicit attitude formation, because there will be more associative evaluation of the stimulus instead of propositional reasoning. Although the investigation of implicit attitudes will be exploratory, I do carefully state this hypothesis:

H4: Consumers that are not instructed to perform thought listing and forecasting will perform less propositional reasoning and more associative evaluation, compared to consumers that are instructed. This will lead to a more positive implicit attitude, and a less positive explicit attitude

Thus, it is expected that instructions have different effects on implicit attitudes than on explicit attitudes, since attitudes can be changed or formed through either the mere association of a valenced stimulus with an attitude object or through more extensive propositional reasoning. It is expected that instructions induce propositional reasoning, while the absence of instructions should lead to more associative evaluation. The APE model suggests that there could be opposite effects between explicit and implicit attitudes and intentions, because propositional reasoning may differ from associative evaluations.

The outcomes of the previous study were a result of an Affect Misattribution procedure (AMP). Misattributions people make about their own affective reactions can be used to measure attitudes implicitly. Combining the logic of projective tests with advances in priming research, the affect misattribution procedure (AMP) is sensitive to normatively favorable and unfavorable evaluations and works at both fast and slow presentation rates (Payne, Cheng, Govorun, & Stewart, 2005). The advantages of the AMP over other implicit association measures such as the Implicit Association Test (IAT) are large effect sizes, high reliability, ease of use, and resistance to correction attempts (Payne et al., 2005). I will use the AMP to test for implicit attitudes.

METHODS

A 2 (Framing: Future vs. Current) x 2 (Elaboration Instructions: Instructions vs. No Instructions)   between-subjects experiment was employed. For the framing manipulation, participants were showed identical ads, except for the time frame. For the instructions manipulation, one half of the participants were instructed to do a thought-listing procedure and a forecasting procedure, the other half did not.

People participated in an online experiment. They were recruited online through Amazon’s Mechanical Turk (http://www.mturk.com) and were paid $1,- for their participation. In total, 200 participants took part in the experiment. Five participants were removed from the data. Either they completed the experiment in less than 5 minutes, or left pauses lasting longer than six minutes between several questions, indicating they did not proceed as required. The remaining 195 participants are 34 years old on average (SD = 11.38), 47% of them are male and half of them have an associate degree or higher.

Procedure

Materials

Ad stimuli. For the experiment, print ads were used as stimuli. The ads contained a picture of

a camera, its brand name (Blackmagic Design), product name ‘4G streaming cinema camera’, logos of ‘4G’, ‘Wi-Fi’ and ‘HD quality’ and a silhouette of a dancing crowd (see appendix I). For the manipulation, the sentence: “In stores now” (current frame) versus “Available in June 2014” (future frame) was included. The study was conducted in the first week of February 2014.

Affect Misattribution Procedure (AMP). The AMP consists of two affect-laden

primes followed by an ambiguous target (a Chinese character). A third prime is a neutral image of a gray square, also followed by the same Chinese character. Participants were instructed to classify the Chinese character as relatively pleasant or unpleasant. Following the pictograph, a pattern mask consisting of black and white “noise” appeared until the participant responded (see Figure 2). In this study, one of the affect-laden primes consisted of images of a Blackmagic Design cameras and the brand logo. The other affect-laden prime consisted of images of products and logo of a competing brand, namely Nikon. In this manner, it was possible to assess participant’s implicit attitudes toward Blackmagic Design, compared to the implicit attitudes toward a competitor, Nikon.

Implicit choice test. Pictures of cameras of five different brands were displayed

(Blackmagic Design, Nikon, Samsung, Canon, Hasselblad). To make sure participants would know of which brand the camera was, the brand name was written down under each picture.

Figure 2. Representative stimuli used in the affect misattribution procedure  

During each trial of the priming task, the prime image appeared in the center of the screen for 75 ms, followed by a blank screen for 125 ms, and then a Chinese pictograph for 100 ms.

All participants were randomly assigned to one of the four conditions of the experiment. They were informed that this was a study of consumer perceptions on advertising and were told to take as much (or as little) time as they wanted to view the ads. When finished with watching the ads, participants completed different questionnaires, depending on the condition they were assigned to. Half of them filled in questionnaires including a thought-listing procedure and affective forecasting instruction, the other half filled in evaluative questions only.

Measures explicit attitudes and intention

Ad-evoked thoughts. All participants in the ‘elaboration instruction’-groups were

assigned to do a thought-listing procedure (Dahlén et al., 2011). Participants were asked to write down their spontaneous thoughts when immediately reacting to the ad and to offer as many (or as few) thoughts as they wanted, without time limit. All thoughts related to either the ad or the product. Mean scores were produced of the number of thoughts per participant (M = 4.67; SD = 2.09; N= 94).

Forecasted feelings. All participants in the ‘elaboration instruction’-groups were

assigned to forecast their feelings (Dahlén et al., 2011). Participants indicated how they thought they would feel after using the advertised product. Three items “excited,” “happy,” and “satisfied” on a seven-point Likert-type scale (anchored by 1 = “completely disagree” and 7 = “completely agree”) were used. Cronbach’s α = .93.

Ad attitude. On the question what did you think about the ad? participants answered

on the three items “bad/good,” “unpleasant/pleasant,” and “unfavorable/favorable,”, on a seven-point Likert-type scale (anchored by 1 = “bad” and 7 = “good” etc.) (Dahlén et al., 2011). Cronbach’s α = .95.

Ad credibility. In the first instance three items “unconvincing/convincing,”

a seven-point Likert-type scale (anchored by 1 = “unbelievable” and 7 = “believable” etc.) (Dahlén et al., 2011). However, together these three produced an averaged index where Cronbach’s α = .56. It appeared that participants did not understand the bias question, probably because it was anchored in the opposite direction. After item was deleted Cronbach’s α = .89.

Ad evaluations. The average of the measures ad-attitude and ad-credibility were used

to measure ad evaluations. Cronbach’s α = .95 (EV = 4.17).

Brand evaluations. Eight items were used to measure brand evaluations (answers

were recorded on a seven-point semantic differential scale varying from 1 - “bad” to 7 - “good” etc.). These were items “bad/good”, “poor quality/high quality”, “dislike/like”, “Inferior/superior”, “unattractive/attractive”, “unpleasant/pleasant”, “boring/interesting”, and “unfavorable/favorable” (Dahlén et al., 2011). Cronbach’s α = .97.

Purchase intention. Three items “interested,” “will try out,” and “want to buy”

(answers were recorded on a seven-point semantic differential scale varying from 1 - “completely disagree” to 7 - “Completely agree”) were used (Dahlén et al., 2011). Cronbach’s α = .93.

All participants completed the Affect Misattribution Procedure (AMP), followed by an implicit choice test. Participants were informed that the study examined “how people make simple but quick judgments.” Participants would see pairs of pictures flashed one after the other, the first one being a real-life image and the second being a Chinese character. They were told that the real-life image simply served as a warning signal for the Chinese character and that they should do nothing with the real-life image. Instead, their job was to judge the visual pleasantness of each Chinese pictograph. Participants were instructed to press the ‘A’ key of their keyboard to indicate ‘unpleasant”, if they judged the Chinese pictograph to be less visually pleasing than average and the ‘L’ key of their keyboard to indicate ‘pleasant’, if they judged it to be more visually pleasing than average. In addition, participants were instructed to respond quickly.

The first set of images was a practice round, so participants could get used to the task first. After the practice round, 36 trials, consisting of 12 Blackmagic Design prime tasks, 12 Nikon prime tasks and 12 neutral prime tasks were presented in a random order. Each trial had a different Chinese character as an ambiguous target. During each trial of the priming task, the prime image appeared in the center of the screen for 75 ms, followed by a blank screen for 125 ms, and then a Chinese pictograph for 100 ms. Following the pictograph, a pattern mask consisting of black and white “noise” appeared until the participant responded. The next trial began as soon as participants made a response. The total task lasted approximately 4 min.

During the implicit choice test, participants were asked to imagine themselves right at the point of purchasing a camera, and to respond as soon as possible to the presented pictures. The pictures were presented on the right and left side of the screen. Participants chose the left picture by pressing the ’A’ key of their keyboard and chose the right picture by pressing the ‘L’ key. On each picture, a camera and a brand name was presented. To make the test less obvious about Blackmagic Design, all possible choice combinations between different cameras were presented, resulting in twenty trials in total.

After completing the questionnaires, the AMP and the implicit choice test, participants were asked what they thought the purpose of the research was. None of the participants correctly identified the purpose of the study.

Measures implicit attitudes and intention

Implicit attitude. First, the AMP-scores were calculated. For the 3x12 trials, I created

proportion scores of pleasantness per prime. Finally, I created a difference-score by subtracting the Nikon AMP-scores from the Blackmagic AMP-scores. This resulted in a score with a minimum of -1 and a maximum of 1 (Payne et al., 2005). The more positive this score, the higher the implicit attitude for Blackmagic Design as compared to Nikon. However, the new scale produced an average index of Cronbach’s α = .38. This will be further discussed in

the discussion. .

Implicit intention The eight trials in which the Blackmagic Design camera was one of the options were recoded to 0=did not choose for Blackmagic Design and 1=chose for Blackmagic Design. A sum score of these eight trials was constructed (M = 3.54, SD = 2.44, N=179) and represents the implicit intention to choose for Blackmagic Design cameras over the other cameras and brands (Eelen, Dewitte, & Warlop, 2013).

RESULTS

Descriptive statistics of all dependent variables for each condition are presented in Table 1. There is a significant, strong positive correlation between the dependent variables: The more positive ad evaluations, the more positive brand evaluations, r = .85, p < .001. The more positive ad evaluations, the more positive purchase intention, r = .65, p < .001, and the more positive brand evaluations, the more positive purchase intention, r = .72, p < .001.

Table 1. Descriptive statistics of dependent variables per condition

Future framing Current framing Instructions M(SD) No instructions M(SD) Instructions M(SD) No instructions M(SD) Ad evaluations _{5.25(1.30) 5.74(.94) 5.25(1.44) 5.22(1.29)} Brand evaluations _{5.38(1.27) 5.49(1.09) 5.23(1.39) 5.06(1.38)} Purchase intention _{4.36(1.99) 4.53(1.67) 4.49(1.67) 4.30(1.74)} N _{44 50 50 51}

Explicit evaluations and intention

The no instructions group scores significantly higher (M = 5.74, SD = .94) than the instructions group (M = 5.25, SD = 1.30), t(92) = -2.13, p = .040. All other scores did not significantly differ between groups.

I performed a multivariate analysis of variance (MANOVA) on the dependent variables. The manipulated time frame (current versus future) had no significant effects on the dependent variables, with ad evaluations F(1, 191) = 2.07, p = .15, η2= .01, brand evaluations

F(1, 191) = 2.50, p = .12, η2 _{= .01, and purchase intention F(1, 191) = .04, p = .85, η}2 _{= .00.}

Therefore, H1 is not supported.

Another MANOVA was performed on the dependent variables with the manipulated instructions (elaboration instructions versus no instructions) as independent variable. Elaboration instructions had no significant effects on the dependent variables, with ad

evaluations F(1, 191) = 1.67, p = .20, η2 _{= .01, brand evaluations F(1, 191) = .03, p = .86, η}2

= .00, and purchase intention F(1, 191) < 1, n.s. η2 = .00. Therefore, H2 is not supported. Two way factorial ANOVA’s were performed to measure the interaction of the instructions manipulation and the framing manipulation. No significant interaction effects were found on the dependent variables, with ad evaluations F(1, 191) = 2.10, p = .15, η2 ₌

.01, brand evaluations F(1, 191) < 1, n.s., η2 = .00, and purchase intention F(1, 191) < 1, n.s., η2 _{= .00. Therefore, H3 is not supported.}

Number of ad-evoked thoughts

I excluded the ‘no instructions’-groups from the analysis (N = 94) and performed multivariate analysis of variance (MANOVA) on the dependent variables. The manipulated time frame (current versus future) had a significant effect on the dependent variable ad evaluations F(1, 92) = 6.20, p = .015, η2 _{= .06. The manipulated time frame had no significant effects on the}

A linear regression analysis (Hayes, 2012) was performed, in a bootstrapping analysis (10.000 samples), to look for mediation of the number of ad-evoked thoughts between the manipulated time frame and the dependent variables. Indirect effects of future framing were found via number of ad-evoked thoughts on all dependent variables. The outcomes are illustrated in Figure 3.

Figure 3. Indirect effects of Future framing via number of ad evoked thoughts

n.s.

Results indicate that there was no significant direct effect of framing on ad evaluations (b = -.23, t = -.83, p = .408). However, there was a significant positive effect of framing on the

number of ad-evoked thoughts (b = 1.05, t = 2.49, p = .014.) and of the number of ad-evoked thoughts on ad evaluations (b = 0.22, t = 3.28, p = .002). Mediation was confirmed in a

bootstrapping analysis (10000 samples) for the number of ad-evoked thoughts (indirect effect = 0.23, 95% CI [0.07, 0.50]).

There was no significant direct effect of framing on brand evaluations (b = -0.05, t = -.17, p = .866), but there was a significant positive effect of framing on the number of

ad-evoked thoughts (b = 1.05, t = 2.49, p = .015.) and of the number of ad-ad-evoked thoughts on brand evaluations (b = 0.19, t = 2.90, p = .005). Mediation was confirmed in a bootstrapping

analysis (10000 samples) for the number of ad-evoked thoughts (indirect effect = 0.20, 95% CI [0.05, 0.44]).

Lastly, there was no significant direct effect of framing on purchase intention (b = -.35, t = -.89, p = .378). However, there was a significant positive effect of framing on the

number of ad-evoked thoughts (b = 1.05, t = 2.41, p = .018.) and of the number of ad-evoked thoughts on purchase intention (b = 0.21, t = 2.22, p = .029). Mediation was confirmed in a

bootstrapping analysis (10000 samples) for the number of ad-evoked thoughts (indirect effect = 0.22, 95% CI [0.04, 0.53]).

To check which thoughts came up in participant’s minds and whether there were differences in the nature of thoughts between the framing groups, I performed an additional content analysis of all the reported thoughts. I coded whether thoughts were about the ad or the product, what their valence was, if they were instrumental or experiential, about the brand,

Temporal Framing (Future vs Current)

Ad evaluations Brand evaluations Purchase intention

Number of ad-evoked thoughts

the costs or time-oriented. Significant differences were found in the number of time-oriented thoughts between the current framing and future framing condition (Mfuture = .13 vs Mcurrent =

0), t(193)= 3.83, p <.001. More specifically, no time-oriented thoughts were reported in the current frame group at all.

Implicit attitudes and intention

First, there was checked for handedness. It could be that right-handed participants indicated pictures as pleasant more often, because it was indexed with their right hand and vice versa for the unpleasant scores for the left-handed participants. No significant differences were found, t(177) = 1.93, p = .06.

In order to test for differences between the prime scores, I performed a 2 (Framing: Future vs. Current) x 2 (Elaboration Instructions: Instructions vs. No Instructions) x 3 (Prime proportion score: Blackmagic Design vs. Nikon vs. Neutral) mixed model repeated measures analysis. Figure 4 shows an overview of the proportion scores per condition.

Figure 4. Proportion scores of pleasantness per prime

The proportion score of “pleasant” responses as a function of prime pleasantness for each condition is presented. Error bars represent one standard error.

The Blackmagic Design proportion scores of pleasantness did not differ significantly across all conditions. A significant effect of elaboration instructions on the Neutral proportion scores was found, F(1, 92) = 4.01, p = .047, η2 = .02. Also, a significant effect of elaboration

instructions on the Nikon proportion scores was found, F(1, 175) = 6.19, p = .014, η2 _{= .03,}

indicating that the Nikon proportion score of pleasantness was significantly higher in the elaboration instructions condition. The subtracted difference-score measuring the implicit attitude (Blackmagic Design proportion score minus Nikon proportion score) is therefore significantly lower in the elaboration instructions condition, because the Nikon proportion score was higher in this group. H4 is therefore supported.

0   0,1   0,2   0,3   0,4   0,5   0,6   0,7   Future framing Instructions Future framing No instructions Current framing Instructions Current framing No instructions

Blackmagic Design prime score

Nikon prime score Neutral prime score

In testing the effects of the instructions condition on implicit intention, no significant direct effect of instructions on implicit intention was found (b = 0.47, t = 1.28, p = .20). However, there was a significant negative effect of instructions on the difference-score of the AMP (b = -1.12, t = -2.71, p = .007) and of the difference-score of the AMP on implicit intention (b = 0.20, t = 3.08, p = .002). Mediation was confirmed in a bootstrap analysis (10000 samples) for the difference-score of the AMP (indirect effect = -0.22, 95% CI [-1.98, 0.05]). Concluding, an indirect effect of elaboration instructions via implicit attitude was found on implicit intention.  

DISCUSSION

This study measured the effects of future framing in advertisements on consumer responses and tested to what extent these effects also occurred spontaneously, if no elaboration instructions were given. Besides, an exploratory investigation on implicit and more associative effects of future framing on consumer behavior followed.

No evidence was found that supports a more positive effect of future framing on ad evaluations, brand evaluations and purchase intention, compared to current framing. Also, no evidence was found that supports a positive effect of instructions on ad evaluations, brand evaluations and purchase intention, and instructions did not moderate the effects of future framing. When zooming in on the instruction-groups of the experiment, participants who were confronted with a future framed ad generated significantly more ad-evoked thoughts. An indirect effect of future framing was found via the number of generated thoughts on ad evaluations, brand evaluations and purchase intention. Although no significant direct effects of future framing were found on evaluations and intention, the amount of generated thoughts in the future framing condition led to more positive ad and brand evaluations towards the product and stronger intention to purchase the product.

The exploratory study gave an interesting insight into the effects of elaboration instructions of the experiment on the implicit attitude and, indirectly, the implicit intention. Evidence for hypothesis 4 was found. Participants that were instructed to list thoughts and to forecast during the experiment indicated the Nikon and neutral primes as significantly more pleasant. The implicit attitude was calculated by subtracting the Nikon and the neutral prime scores from the Blackmagic Design prime score. This resulted in a less positive implicit attitude for Blackmagic Design in the elaboration instructions condition. Subsequently, participants that were not instructed indicated the Nikon and Neutral primes as significantly less pleasant, resulting in a more positive implicit attitude for Blackmagic Design. An indirect effect of instructions was found via the implicit attitude on the implicit intention. No effects of future framing were found on implicit attitude or implicit intention.

Results are opposite of previous studies

The results of this study do not correspond with previous studies on the effect of future framing (Martin et al., 2009; Dahlén et al., 2011). They are not in line with theoretical expectations from construal level theory, suggesting that temporal distance causes consumers to evaluate a product more favorably as positive attributes become more salient at distance, whereas negative aspects related to the product are suppressed and less focal (Trope & Liberman, 2003). Although no significant results were found during hypotheses testing, some interesting and contradictory findings should be given some extra thoughts. These findings are discussed below.

Future framing generates significantly more thoughts than current framing. Zooming in within the instructions condition during the analyses, showed that future framing had a significant effect on number of thoughts and that an indirect effect via the number of thoughts on ad evaluations, brand evaluations and purchase intention was found. A content analysis of the thoughts showed that there were not only more thoughts in the future framing condition, they also were significantly more frequently about the future time frame (“I can’t wait until

it’s June”, “June is only a few months from now”, etc.). The results confirm what was found

in the study of Dahlén et al. (2011): A future frame generates more and positive thoughts about the future (Trope & Liberman, 2003).

Results on implicit testing

As earlier stated, all implicit attitude scores for the Blackmagic design brand were highly positive on average in all the experimental groups. No significant differences were found between the implicit attitude scores of Blackmagic Design across conditions, but of all prime scores in each group, Blackmagic Design scored highest. What does this mean?

The effects of repeated message exposure in marketing have traditionally been studied in the context of attitude change theories, such as "mere exposure" (Sawyer, 1981). The widely accepted explanation for mere exposure results is that with ads that are relatively hard to process, it takes a number of repetitions for individuals to fully comprehend and process the message. Because everyone was exposed to a Blackmagic ad for at least five seconds at the beginning of the experiment, and every participant saw images of Blackmagic Design again during the AMP procedure, it is arguable that the repeated exposure to the ad caused a mere exposure effect. According to previous research, mere exposure effects are thought to explain the process by which peripheral cues influence attitudes (Lien, 2001). Implicitly, via peripheral cues, the implicit attitude could arguably be influenced by a repeated exposure to Blackmagic Design images.

Although this exploratory part of the study focused on finding implicit effects of future framing on attitude change, I did not find such effects. However, I did find significant positive effects of instructions on implicit attitude. No instructions led to significantly more positive implicit attitudes towards Blackmagic Design. Moreover, elaboration instructions significantly led to more pleasant response to primes of the competitor brand, Nikon. The absence of elaboration instructions probably led to less propositional reasoning and more associative evaluation, resulting in the more positive implicit attitudes toward the product.

Limitations and further research

There are a number of limitations to this study that need to be addressed. First, no pretest was performed to test the stimulus materials. However, in order to still get some interpretation about the validity and reliability of the stimulus materials, I used the reported thoughts of the participants. Several thoughts indicated the professional look of the ad, the appealing color scheme and the way in which this ad was ‘typical for a camera product’. Also, the difference between the future framed ad and the current ad was seen in the number and nature of thoughts about time that were induced when a future frame was used, compared to when a current frame was used. However, there were also some thoughts indicating the unlikelihood that this was a real ad. Concluding, it would have been more appropriate if the stimulus materials had been pretested prior to the conduction of the experiment.

A second limitation to this study is that the reliability of the AMP-difference score scale was questionable. Results of the AMP in relation with the implicit measure for intention should therefore be interpreted with great caution, because the reliability of the AMP-difference score was very low. One of the reasons for the low amount of reliability is that several prime tasks were identical to each other, meaning that the same images of the brands and cameras were used. According to Payne et al. (2005), it is essential that all prime tasks in the AMP differ from each other. However, it was very hard to find twelve distinctively different pictures of the Blackmagic Design and cameras.

Another important limitation is that the AMP was carried out in an online environment. Even though the AMP is the most suitable implicit attitude test to be performed online, it remains unclear which participants filled in the test incorrectly, due to a bad Internet connection. Next to the connectivity issue, there was little environmental control as a researcher on what participants were doing next to participating in this study. It is hard to overcome these restraints when conducting online experiments. However, by keeping track of participant’s behavior via a timer on each part of the experiment, it was possible to check whether participants were involved in the study. Besides, participants were asked at the end of the experiment whether they have been in a distracting environment or not.

Unfortunately, there was not taken enough advantage of the timers during the experiment. With use of the timers recording the amount of time during the exposure to the ads, I could have tested to what extent the amount of time spend watching the ad could influence the effects of future framing on both explicit and implicit outcomes. The mere exposure effect mentioned earlier is dependent on the amount of time people are exposed to an ad (Sawyer, 1981). Future research should take into account the time spend watching the ad in their analyses.

The final limitation of this research and, and of its predecessors, is that very little is known about the field of future framing so far. It is therefore very hard to find theoretical explanations and evidence supporting my reasoning and hypotheses. Future studies are needed to generate more knowledge about future framing in advertising. Even if a strong bias towards future products actually exists, this study found opposite results. Future research should focus more on measuring the time spend watching the ad, and should test in more natural environments. Also, more time variation in temporal distance (not only ‘in stores now’ and in ‘half a year’, but also ‘next week’, ‘in the end of 2020’ etc.) could be used. Besides, psychological differences can be interesting moderators on the effects of temporal framing. For example, people who are more future-oriented might significantly have more thoughts about the future than someone who is not future oriented. This might interact with both future framing as the elaboration instructions.

Managerial implications

While this investigation focused on preannounced product advertising and found no to little results, I believe that something like a future bias might exist. The successes of the iPhone and other phenomena such as the Guns N’ Roses perpetually forthcoming “Chinese Democracy” album could not be ascribed to being simply ‘a lucky shot’. According to this study, not the temporal framing, but the presence or absence of instructions might possibly have some influence on your sales. Foremost, it is important to assess the strong assumptions made in books like ‘Nextopia’ about the effects of future framing in advertising with great caution. Too little is known about the effects of future framing in different conditions, and it has not been tested in natural environments.

Another implication lies in the elaboration instructions and how they affect implicit attitudes negatively. With regard to the ongoing debate in marketing communication about ‘consumer engagement’ (Chu & Kim, 2011; Brodie, Illic, Juric, & Hollebeek, 2013), this article might suggest that no elaboration on your product or brand, but just a mere exposure, works better in influencing implicit consumer attitudes. We are living in a very brand-cluttered society, where companies are fighting for the attention of the consumer. Maybe the best strategy is not to strive for more consumer engagement, but to find smart ways to

increase mere exposure of your brand. This could be achieved with brand or product placements (Redker, Gibson, & Zimmerman, 2013), but also priming and nudging strategies in store environments would apply here. As long as there are rapid, short exposures to the persuasive message, a mere exposure effect could arise and this could affect implicit attitudes.

Concluding this study, according to existing theory and research, consumers do seem to be systematically biased to view forthcoming products as general improvements over currently available products, even when there are no factual claims to support such expectations (Sorescu et al., 2007; Dahlén et al., 2011; Trope & Liberman, 2003). However, such a result was not found in this study. What if other factors could have contributed to the success of prelaunched products in previous studies? Was its success really because of the effects of future framing, and did it really result in the activation of more thoughts about our future? How real is this future, or better stated ‘distance’, we imagine anyway? Has Albert Einstein always been right when he stated: “The distinction between thepast, present and future is only a stubbornly persistent illusion”? Hopefully, time will tell.

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APPENDIX I – Stimulus materials

Examples Prime task images of the AMP